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PROTECT: Protein circadian time prediction using unsupervised learning
Aram Ansary Ogholbake1, Qiang Cheng1
1Department of Internal Medicine and Department of Computer Science, University of Kentucky, Lexington, KY, USA.
Iscience
|October 23, 2025
Summary
Circadian rhythm disruption is linked to Alzheimer's disease (AD). A new deep learning method, PROTECT, analyzes proteomic data without time labels to reveal significant circadian changes in AD patients.
Area of Science:
- Chronobiology
- Neuroscience
- Proteomics
- Artificial Intelligence
Background:
- Circadian rhythms govern human physiology, and their disruption is implicated in diseases such as Alzheimer's disease (AD).
- Proteomic datasets often lack crucial time-label information, presenting significant challenges (small samples, high dimensionality, noise) for circadian rhythm analysis.
Purpose of the Study:
- To introduce PROTECT, an unsupervised deep learning method for predicting circadian sample phases from unlabeled proteomic data.
- To apply PROTECT to identify circadian disruptions in Alzheimer's disease (AD) using postmortem human brain and urine proteomic data.
- To compare circadian patterns between AD and control subjects to understand AD-related circadian dysregulation.
Main Methods:
- Developed PROTECT, an unsupervised deep learning algorithm utilizing greedy layer-wise pre-training and cosine-based fine-tuning.
- Validated PROTECT's accuracy on existing time-labeled proteomic datasets.
- Applied PROTECT to unlabeled human proteomic data from postmortem brain regions and urine samples.
Main Results:
- PROTECT accurately predicts circadian sample phases without requiring time labels or prior knowledge of rhythmic proteins.
- Analysis of AD proteomic data revealed significant circadian disruptions, identifying proteins with retained, lost, or altered rhythmicity.
- Proteins maintaining rhythmicity exhibited region-specific phase shifts and amplitude changes; enrichment analysis provided functional insights into altered rhythmicity.
Conclusions:
- PROTECT is an effective tool for circadian analysis of unlabeled proteomic data, overcoming common dataset limitations.
- The study provides systematic evidence of circadian pattern alterations in Alzheimer's disease (AD) brain and urine proteomic data.
- Findings highlight key proteins and functional pathways involved in AD-related circadian dysregulation, offering potential therapeutic targets.
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